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MSUU14 2009
Exercise 5
The idea of this exercise is to estimate inoptimality losses (or Expected Value of Perfect Information,
EVPI) due to random errors in simulation input data (ie. forest inventory errors). The simulation &
optimization proceeds in three steps:
1. Simulating & optimizing the true optimal estate-level harvest schedule (ie. normal
simulation and optimization)
2. Simulating and optimizing a large number of realizations with random errors in the input
data (ie. Monte Carlo –type simulation)
3. Simulating NPV estimates for the harvest schedules generated in step 2.
After these three steps, you will calculate the absolute and relative losses at single stand-level and at
estate-level. Finally, you will carry out a simple analysis of the results and write a brief report.
Setting up SIMO
For installing SIMO on your computer, building your simulator and running the simulations, please
refer to the instructions of Exercise 1.
The materials for this exercise you can find from MOODLE. Download the new SIMO package and
install it in similar way to exercise 1.
Running the simulations and optimizations
Step 1.
In step 1 you will run a normal simulation and optimization, which will yield the true optimal, or
reference, harvest schedules. To complete step 1, just build and run simo and answer the questions:
> bin\builder.exe build exec5\builder.ini
> bin\runner.exe exec5\runner_I.ini
What is the optimization task objective?
What are the constraints like?
Step 2.
In step 2 you will run a simulation similar to that in step 1, but with two exceptions. First, random
errors are generated into the input data from a normal univariate distributions, where mean =0.0%
and standard deviation =20.0%. Secondly, the whole simulation and optimization process is
repeated 30 times for each stand in order to get a decent sample of the loss distribution of each
stand. To complete step 2, just build and run simo:
> bin\runner.exe exec5\runner_II.ini
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Step 3.
In step 3 you will simulate a 30-year development of each harvest schedule generated in step 2, but
without generating the random errors into the input data, ie. use the timings of the operations from
step 2. No optimization is done in step 3, as the timings of the harvests for each realization of each
stand has been scheduled in step 2. To complete step 2, just build and run simo:
> bin\runner.exe exec5\runner_III.ini
Analyzing the results
After completing steps 1, 2 and 3 you should have now the true optimal NPV estimates from step I,
the harvest schedules affected by random input data errors from step II and the (inoptimal) NPV
estimates based on the erroneous harvest schedules from step III.
All the results should be stored in various SIMO output files in folders output_I, output_II and
output_III. In each of these folders, there should be a file named NPV.txt. In exec5 folder you should
find a small python script named losses.py that will handle the processing of the results for you. You
can run the program by typing:
> python exec5/losses.py
Now, a folder named losses with a file named losses.txt should appear in exec5 folder. Open the file
and copy the contents to Excel. In order to analyze the losses you will need also the initial stand-level
attribute values. To get them, run:
> bin\runner.exe exec5\runner_init.ini
The above command should compute and output the initial stand attributes and store them into
folder output_init. Open the file initial_values.txt and copy the contents also to the same Excel sheet
as the stand-level losses. Next, examine the relative of the losses and the various stand-level
attribute values (eg. Age, BA, V, N, H_dom…). Write a short description on what stand-level
attributes seem to have a distinct relation with the stand-level losses (include some graphs that
show the relation). Answer also the following questions. NOTE! The stand-level initial attribute
values are already per hectare, but the losses and NPV estimates from the file losses.txt are per
stand (you need to convert the values as per hectare).
What is the average loss per hectare in euros?
What is the average relative loss per hectare in percent?